Traditional treatment for type 1 diabetes mellitus （T1DM） primarily involves insulin replacement， yet some patients encounter issues such as significant blood glucose fluctuations， high risk of hypoglycemia， and weight gain. In recent years， the adjuvant therapeutic role of non-insulin hypoglycemic drugs in T1DM has gradually gained attention. This article reviews the mechanisms of action and clinical research progress of five types of non-insulin hypoglycemic drugs in the treatment of T1DM： amylin analogues （pramlintide）， biguanides （metformin）， sodium-glucose co-transporter 2 inhibitor， dipeptidyl peptidase-4 inhibitor， and glucagon-like peptide-1 receptor agonist. It is found that these drugs can enhance clinical benefits for T1DM patients by improving insulin sensitivity， delaying gastric emptying， promoting urinary glucose excretion， and regulating incretin levels， thereby reducing glycated hemoglobin levels， decreasing insulin dosage， and managing body weight. Simultaneously， these drugs also present limitations such as low patient compliance due to complex dosing regimens， increased risk of diabetic ketoacidosis， and heterogeneity in glycemic control. Future research could focus on developing individualized treatment strategies， combining pharmacogenomics with novel biomarkers to precisely identify subpopulations of patients who may benefit， and delving into the potential value of these drugs in delaying diabetic vascular complications and improving patients’ quality of life.

Objective To explore the wearing status and actual noise reduction effect of hearing protectors among noise workers in a typical automobile manufacturing enterprise. Methods In April 2024, an occupational hazard factor testing was carried out in an automobile manufacturing industry, and at the same time, the hearing protection fit test was conducted for noise workers. Intervention and guidance were provided to those who did not pass the minimum standard of baseline PAR. The difference in PAR between baseline and post-intervention was compared, and the effectiveness of hearing protector wearing method training was evaluated. Results The exceeding rate of the company's noise operation post was 50.77% (66/130). The baseline PAR of the subjects with working experience of less than 15 years and wearing hearing protectors throughout noisy work was higher, and the differences were statistically significant (P<0.05). Compared with those with 80dB≤L_{EX, 8h}<85dB, more research subjects with L_{EX, 8h}≥85dB failed baseline PAR (39.13%). After intervention, the PAR of the subjects who did not pass the minimum standard of baseline PRA increased from 2.0 (0.0, 5.3) to 17.0 (14.8, 20.0), and the protection level was significantly improved, and the difference was statistically significant (P<0.01). Conclusion The individual fit test of hearing protector is an important means to evaluate the actual noise reduction level of hearing protector and guide the selection of hearing protection models. Corporate training can help improve the PAR of hearing protectors.

ObjectiveTo explore the effect of piercing electroacupuncture on ankle muscle strength, dynamic balance and subjective stability in patients with functional ankle instability (FAI). MethodsA total of 48 patients with FAI admitted to the Affiliated Hospital of Traditional Chinese Medicine, Shandong Second Medical University from April, 2024 to July, 2025 were enrolled and randomly divided into control group (n = 24) and experimental group (n = 24). The control group received multimodal functional training, while the experimental group received piercing electroacupuncture in addition, for six weeks. Relative peak torque of ankle plantarflexion, dorsiflexion, inversion and eversion were measured with isokinetic muscle strength testing system before and after treatment, while Y-Balance Test (YBT) and Cumberland Ankle Instability Tool (CAIT) were adopted for evaluation. ResultsOne case dropped out in each group. Relative peak torque of ankle plantarflexion, dorsiflexion, inversion and eversion at each angular velocity, the normalized distance in each direction and composite score of YBT, as well as the score of CAIT increased in both groups after treatment (|t| > 2.891, P < 0.01), while all the indicators were better in the experimental group than in the control group (|t| > 2.104, P < 0.05), except dorsiflexion muscle strength. ConclusionCombination of piercing electroacupuncture can further improve perimalleolar muscle strength, dynamic balance and subjective stability in patients with FAI.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To explore the predictive value of artificial intelligence (AI)-based lung nodule CT quantitative analysis for the invasion degree of lung adenocarcinoma spectrum lesions. Methods According to the invasion degree of lung adenocarcinoma spectrum lesions, patients with surgically and pathologically confirmed lung adenocarcinoma spectrum lesions from January to June 2023 in Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University were retrospectively collected and divided into a non-invasive group and an invasive group, including atypical adenomatous hyperplasia, adenocarcinoma in situ, and minimally invasive adenocarcinoma patients in the non-invasive group, and invasive adenocarcinoma patients in the invasive group. All enrolled patients underwent chest CT before surgery, and then the lung nodules were quantitatively analyzed using an AI-based computer-aided diagnosis system to compare the related quantitative parameters of lung nodules that have been surgically removed and pathologically confirmed as lung adenocarcinoma spectrum lesions between the two groups. The relationship between various CT quantitative features and the invasion degree of lung adenocarcinoma spectrum lesions was analyzed. Results A total of 149 patients (149 lesions) were included, including 42 males and 107 females, aged 29-81 (56.35±10.75) years. There were 72 patients in the non-invasive group and 77 patients in the invasive group. Statistical differences were observed between the two groups in long diameter, short diameter, volume, surface area, mass, maximum cross-sectional area, 3D long diameter, maximum CT value, minimum CT value, average CT value, entropy, kurtosis, skewness, malignancy probability and other indicators (P<0.05). Multivariate binary logistic regression analysis showed that long diameter [OR=1.687, 95%CI (1.364, 2.085), P<0.001], average CT value [OR=1.006, 95%CI (1.002, 1.009), P=0.002], and malignancy probability [OR=1.034, 95%CI (1.005, 1.063), P=0.020] were independent risk factors for the invasion degree of lung adenocarcinoma. The predictive model combining the above parameters demonstrated optimal performance, with an area under the receiver operating characteristic curve of 0.951, sensitivity of 0.818, and specificity of 0.972. Using a Nomogram to quantify the three independent risk factors, the cross-validation was performed to evaluate the stability of the model, and the average C-index of cross-validation was 0.950, with each fold C-index >0.75, indicating that the prediction performance of the model was stable, and the calibration curve and decision curve indicated good predictive performance. Conclusion The visualization prediction model constructed by AI-based quantitative analysis of lung nodules in CT demonstrates significant discriminative effectiveness in the assessment of invasiveness in lung adenocarcinoma spectrum lesions. This visualization prediction model can provide a quantitative decision-making basis for the preoperative identification of the degree of invasiveness in lung adenocarcinoma spectrum lesions.

Objective To analyze the increase in hearing thresholds in different frequency bands of workers exposed to different characteristic noises and the influencing factors of binaural high-frequency hearing loss, and to provide theoretical support for occupational health monitoring in enterprises. Methods In 2021, noise-exposed workers were selected from typical noise-exposing enterprises as research subjects, and their occupational health examination data were tracked for three consecutive years. According to the on-site detection from 2021 to 2023, the cumulative noise exposure (CNE) was calculated. The chi-square test was used to compare the increase of the hearing threshold of workers exposed to different characteristic noises in different frequency bands. A generalized estimation equation was constructed to explore the influencing factors of high-frequency hearing loss in the research subjects. Results The age of the study subjects was 23-54 years old, with 1.6-20.1 years of working experience, mainly distributed in manufacturing workshops, technical workshops and public works workshops. The median LAeq,8h was 85.90 (84.5, 86.1) dB(A), and the average CNE was 94.3±2.6 dB(A). The number of people with increased hearing thresholds in each frequency band was 0.5kHz>6kHz>4kHz>3kHz>1kHz>2kHz. There were statistically significant differences in the increase of hearing thresholds in each frequency band, binaural speech frequency impairment, and high-frequency hearing loss among subjects with different characteristics (P<0.05). The detection rate of binaural speech frequency hearing loss was the highest in subjects aged>45 years, with a length of service of>15 years, and with a CNE>96dB(A). The detection rate of binaural high-frequency hearing loss was the highest in subjects aged 35-40 years, with a length of service of 5-10 years, and with a CNE>96dB(A).In addition, the detection rate of binaural speech frequency and high-frequency hearing loss increased with the increase of CNE(P<0.05). The GEE model showed that age>40 years and CNE>96dB(A) were risk factors for high-frequency hearing loss in both ears. Conclusion With increasing age and CNE, hearing thresholds rise across all frequency bands, elevating the risk of binaural speech-frequency and high-frequency hearing loss, thereby increasing the likelihood of occupational noise-induced deafness.

Objective To examine the impact of climate, land use and their interaction effect on the population density of Oncomelania hupensis. Methods O. hupensis snail surveillance data in Yunnan Province from 2013 to 2022 were obtained from the National Information System for Parasitic Diseases Prevention and Control of Chinese Information System for Disease Control and Prevention, and the density of living snails was calculated in each county-level administrative district. Climate data were obtained from the China Meteorological Forcing Dataset version 2.0, and land use data were captured from the China Land Cover Dataset. The raster climate data and land use data were clipped to the administrative border of Yunnan Province in the R package version 4.5, and the climate data were resampled to a spatial resolution of 30 m × 30 m consistent with the land use data using bilinear interpolation. Annual meteorological indicators were extracted from each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022, including average temperature, maximum temperature, minimum temperature, temperature difference, average precipitation rate, maximum precipitation rate, minimum precipitation rate, downward shortwave radiation flux, downward longwave radiation flux, air pressure, wind speed, specific humidity and relative humidity. Annual land use structure and landscape pattern index in each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022 were extracted and calculated, including the proportion of areas occupied by each type of land use, patch density, largest patch index, landscape separation index, landscape fragmentation index, landscape segmentation index, contagion index, patch cohesion index, edge density, and shape index. Land use entropy index was introduced to represent the degree of habitat fragmentation and ecological niche breadth. The density of living snails and environmental factors were subjected to rank correlation analysis, and variables with no statistically significant correlation (P>0.1) were excluded. Then, a correlation coefficient matrix was constructed, and |r_s| of 0.85 and greater was defined as the threshold of high collinearity. For highly correlated variables in each group, indicators with a more biological explanatory power or a better statistical efficiency were retained. A generalized additive model (GAM) was constructed with O. hupensis snail density as a response variable and screened environmental variables as independent variables, and the model performance was evaluated using the variance explained. Results The area occupied by O. hupensis snail habitats was 1 056 to 1 680 hm² in Yunnan Province from 2013 to 2022, appearing an overall tendency towards a decline; however, the density of living snails appeared a tendency towards a slight rise. Based on the correlation coefficient matrix, 14 core explanatory variables were retained, including farmland, water bodies, bare land, impervious surface, landscape separation index, landscape fragmentation index, edge density, shape index, land use entropy index, downward longwave radiation flux, downward shortwave radiation flux, maximum temperature, minimum precipitation rate and specific humidity. Two types of GAM were constructed, including the main-effects model without interaction terms and the interaction model with interaction terms. The corrected Akaike information criterion (AICc) of the optimal main-effects model was −285.223, and the core variables included bare land, impervious surface, landscape separation index, edge density, shape index, land use entropy index and downward shortwave radiation flux. Following introduction of second-order interaction terms, the AICc value of the optimal interaction model was −345.526, and the significant interaction combinations included: farmland × impervious surface, farmland × landscape separation index, farmland × shape index, farmland × land use entropy index, impervious surface × landscape separation index, impervious surface × edge density, and shape index × downward shortwave radiation flux. The proportion of the main-effects model explaining the variation of O. hupensis snail density was 39.8%, and the explanatory power of GAM increased to 79.0% following introduction of interaction terms. Conclusion Landscape separation index, edge density, shape index and other landscape pattern indicators pose significant impacts on the intensity and direction of changes in O. hupensis snail density in Yunnan Province.

ObjectiveColorectal cancer (CRC) is a highly heterogeneous malignancy, and traditional Chinese medicine (TCM) syndrome differentiation is widely used in its clinical management. However, the biological basis underlying different TCM syndromes remains insufficiently understood. This study aimed to investigate the proteomic differences between qi-blood deficiency syndrome (QBDS) and damp-heat syndrome (DHS) in CRC patients and to establish a “syndrome-differential protein-herbal component” network for exploring potential molecular mechanisms and therapeutic targets associated with syndrome-specific treatment strategies. MethodsTumor tissue samples were collected from 10 patients with pathologically confirmed CRC, including 5 patients diagnosed with QBDS and 5 with DHS according to standardized TCM syndrome differentiation criteria. Tandem mass tag (TMT)-based quantitative proteomics was employed to identify differentially expressed proteins (DEPs) between the two syndrome groups. Functional enrichment analyses, including Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, were performed to characterize the biological functions and signaling pathways associated with the identified DEPs. Least absolute shrinkage and selection operator (LASSO) regression analysis was further applied to screen key syndrome-related proteins and construct a core protein prediction model. Subsequently, molecular docking was conducted to evaluate the binding affinities between representative herbal compounds, astragaloside IV and berberine, and the identified core proteins. Finally, cell counting kit-8 (CCK-8) assays were performed in HCT 116 and HT-29 colorectal cancer cell lines to validate the anti-proliferative activities of these compounds in vitro. ResultsA total of 44 DEPs were identified between QBDS and DHS tissues, including 21 upregulated and 23 downregulated proteins in the QBDS group relative to the DHS group. Functional enrichment analyses revealed that these proteins were primarily associated with antiviral immune responses, regulation of inflammatory signaling, NF‑κB signaling pathways, cholesterol metabolism, and other biological processes relevant to tumor progression and host immune regulation. LASSO regression analysis identified eight core proteins with potential syndrome-specific significance. Among them, ST7, GPCPD1, and PODXL were closely associated with QBDS, whereas FAT1, GRB7, KRT7, MAFF, and MMP8 were associated with DHS. Molecular docking demonstrated favorable interactions between astragaloside IV and QBDS-related proteins, with binding energies lower than -5 kcal/mol, indicating stable binding activity. Berberine exhibited even lower binding energies and stronger binding specificity toward DHS-related core proteins. In vitro experiments further confirmed that both compounds inhibited CRC cell proliferation, while berberine displayed significantly greater anti-proliferative efficacy. The lowest 48 h IC₅₀ value of berberine reached 15.21 mg/L in CRC cells, indicating a stronger growth-inhibitory effect than astragaloside IV. ConclusionCRC patients with QBDS and DHS exhibit distinct proteomic characteristics, suggesting that different TCM syndromes possess unique molecular signatures. The identified core proteins may serve as potential biomarkers for syndrome differentiation, while astragaloside IV and berberine may exert therapeutic effects through targeting syndrome-specific molecular networks. These findings provide preliminary proteomic evidence supporting syndrome-guided precision integrative medicine in CRC and offer new insights into the biological basis of TCM syndrome differentiation and individualized therapeutic strategies.

Objective To investigate changes in the distribution of Oncomelania hupensis snails in Yixing City, Jiangsu Province, from 2008 to 2024, and to provide insights to guide formulation of O. hupensis snail investigation and surveillance programs. Methods Data from O. hupensis snail surveys in Yixing City from 2008 to 2024 were collected. Trends in snail habitat site numbers, snail-infested areas, proportion of total area with snail habitats, occurrence of frames with living snails, and density of living snails in snail habitats in hilly regions of Yixing City were evaluated from 2008 to 2024 by applying a Joinpoint regression model to collect annual percent change (APC) and average annual percent change (AAPC) data. Results From 2008 to 2024, a total of 193.815 hm2 of snail-infested area was found within Yixing City, of which 191.765 hm2 (accounting for 98.94%) was distributed in hilly regions. A total of 344 snail infestation sites in hilly regions were identified. The average occurrence rate of living snail frames in snail habitats was 8.650% and the average living snail density in snail habitats was 0.246 per 0.1 m2. No Oncomelania snails were positively identified. The number of snail habitat sites in hilly regions of Yixing City showed no significant decreasing trend (AAPC=-2.8%, P=0.527). Similarly, no significant increasing trend in snail-infested area (APC=AAPC=5.7%, P=0.328) was found. The occurrence rate of living snail frames in snail habitats showed no significant increasing trend (APC=AAPC=5.1%, P=0.583). Living snail density in snail habitats also showed no significant increasing trend (APC=AAPC=3.2%, P=0.598). Conclusions From 2008 to 2024, snail infestation has persisted in the hilly areas of Yixing City with an unclear variation trend. The quality of snail investigation and snail surveillance system should be strengthened to permit timely identification of hidden dangers and rapid risk responses, thereby preventing schistosomiasis outbreaks.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.